Is deep-learning-drizzle open source?

Yes — kmario23/deep-learning-drizzle is an open-source project tracked on heatdrop.

What language is deep-learning-drizzle written in?

kmario23/deep-learning-drizzle is primarily written in HTML.

How popular is deep-learning-drizzle?

kmario23/deep-learning-drizzle has 12.9k stars on GitHub.

Where can I find deep-learning-drizzle?

kmario23/deep-learning-drizzle is on GitHub at https://github.com/kmario23/deep-learning-drizzle.

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kmario23/deep-learning-drizzle

A Curated Flood of Free AI Lectures

Because the best deep learning courses are scattered across university YouTube channels and torrent trackers, and nobody wants to hunt for Hinton's slides.

★12.9k stars HTML Learning

View on GitHub ↗ Homepage ↗

Not currently ranked — collecting fresh signals.

star history

What it does

This is a curated directory of free university lecture series covering deep learning, reinforcement learning, computer vision, NLP, and a dozen adjacent AI subfields. It organizes links to course homepages, YouTube playlists, and Academic Torrent mirrors into dense thematic tables—essentially a community syllabus for self-directed learners.

The interesting bit

There is no software here, just editorial labor: the maintainer has corralled scattered classic courses—Hinton’s 2012 Toronto lectures, Karpathy’s CS231n, Socher’s CS224n—into one bookmarkable README. In a field drowning in blog posts and paywalled certificates, it treats raw university recordings as the canonical curriculum.

Key highlights

15+ topic sections, including niche areas like geometric deep learning, medical imaging, and probabilistic graphical models.
Direct links to primary sources: course pages, YouTube playlists, and torrent mirrors.
Historically significant series are preserved, dating from 2012 through the mid-2010s Stanford deep-learning boom.
12,818 stars suggest it functions as a de facto community index.

Caveats

The README is one enormous markdown file padded with emoji dividers, so browsing can feel like scrolling through a very long syllabus.
Many visible entries skew toward 2012–2017; the README truncation makes it hard to judge how actively newer courses are being added.
It is a static link list—no search, tagging, or interactive filtering.

Verdict

Worth a star if you are self-studying AI and want a structured starting point for free, authoritative lectures. Skip it if you are looking for runnable code, datasets, or a modern course platform.

Frequently asked

What is kmario23/deep-learning-drizzle?: Because the best deep learning courses are scattered across university YouTube channels and torrent trackers, and nobody wants to hunt for Hinton's slides.
Is deep-learning-drizzle open source?: Yes — kmario23/deep-learning-drizzle is an open-source project tracked on heatdrop.
What language is deep-learning-drizzle written in?: kmario23/deep-learning-drizzle is primarily written in HTML.
How popular is deep-learning-drizzle?: kmario23/deep-learning-drizzle has 12.9k stars on GitHub.
Where can I find deep-learning-drizzle?: kmario23/deep-learning-drizzle is on GitHub at https://github.com/kmario23/deep-learning-drizzle.